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\section{Fizhi: High-end Atmospheric Physics} |
\subsection{Fizhi: High-end Atmospheric Physics} |
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\label{sec:pkg:fizhi} |
\label{sec:pkg:fizhi} |
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\input{texinputs/epsf.tex} |
\input{texinputs/epsf.tex} |
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\subsection{Introduction} |
\subsubsection{Introduction} |
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The fizhi (high-end atmospheric physics) package includes a collection of state-of-the-art |
The fizhi (high-end atmospheric physics) package includes a collection of state-of-the-art |
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physical parameterizations for atmospheric radiation, cumulus convection, atmospheric |
physical parameterizations for atmospheric radiation, cumulus convection, atmospheric |
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boundary layer turbulence, and land surface processes. |
boundary layer turbulence, and land surface processes. The collection of atmospheric |
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physics parameterizations were originally used together as part of the GEOS-3 |
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(Goddard Earth Observing System-3) GCM developed at the NASA/Goddard Global Modelling |
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and Assimilation Office (GMAO). |
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% ************************************************************************* |
% ************************************************************************* |
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% ************************************************************************* |
% ************************************************************************* |
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\subsection{Equations} |
\subsubsection{Equations} |
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\subsubsection{Moist Convective Processes} |
Moist Convective Processes: |
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\paragraph{Sub-grid and Large-scale Convection} |
\paragraph{Sub-grid and Large-scale Convection} |
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\label{sec:fizhi:mc} |
\label{sec:fizhi:mc} |
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Sub-grid scale cumulus convection is parameterized using the Relaxed Arakawa |
Sub-grid scale cumulus convection is parameterized using the Relaxed Arakawa |
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Schubert (RAS) scheme of Moorthi and Suarez (1992), which is a linearized Arakawa Schubert |
Schubert (RAS) scheme of \cite{moorsz:92}, which is a linearized Arakawa Schubert |
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type scheme. RAS predicts the mass flux from an ensemble of clouds. Each subensemble is identified |
type scheme. RAS predicts the mass flux from an ensemble of clouds. Each subensemble is identified |
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by its entrainment rate and level of neutral bouyancy which are determined by the grid-scale properties. |
by its entrainment rate and level of neutral bouyancy which are determined by the grid-scale properties. |
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mass flux, is a linear function of height, expressed as: |
mass flux, is a linear function of height, expressed as: |
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\[ |
\[ |
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\pp{\eta(z)}{z} = \lambda \hspace{0.4cm}or\hspace{0.4cm} \pp{\eta(P^{\kappa})}{P^{\kappa}} = |
\pp{\eta(z)}{z} = \lambda \hspace{0.4cm}or\hspace{0.4cm} \pp{\eta(P^{\kappa})}{P^{\kappa}} = |
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-{c_p \over {g}}\theta\lambda |
-\frac{c_p}{g}\theta\lambda |
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\] |
\] |
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where we have used the hydrostatic equation written in the form: |
where we have used the hydrostatic equation written in the form: |
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\[ |
\[ |
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\pp{z}{P^{\kappa}} = -{c_p \over {g}}\theta |
\pp{z}{P^{\kappa}} = -\frac{c_p}{g}\theta |
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\] |
\] |
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|
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The entrainment parameter, $\lambda$, characterizes a particular subensemble based on its |
The entrainment parameter, $\lambda$, characterizes a particular subensemble based on its |
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detrainment level, and is obtained by assuming that the level of detrainment is the level of neutral |
detrainment level, and is obtained by assuming that the level of detrainment is the level of neutral |
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buoyancy, ie., the level at which the moist static energy of the cloud, $h_c$, is equal |
buoyancy, ie., the level at which the moist static energy of the cloud, $h_c$, is equal |
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to the saturation moist static energy of the environment, $h^*$. Following Moorthi and Suarez (1992), |
to the saturation moist static energy of the environment, $h^*$. Following \cite{moorsz:92}, |
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$\lambda$ may be written as |
$\lambda$ may be written as |
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\[ |
\[ |
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\lambda = { {h_B - h^*_D} \over { {c_p \over g} {\int_{P_D}^{P_B}\theta(h^*_D-h)dP^{\kappa}}} } , |
\lambda = \frac{h_B - h^*_D}{ \frac{c_p}{g} \int_{P_D}^{P_B}\theta(h^*_D-h)dP^{\kappa}}, |
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\] |
\] |
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|
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where the subscript $B$ refers to cloud base, and the subscript $D$ refers to the detrainment level. |
where the subscript $B$ refers to cloud base, and the subscript $D$ refers to the detrainment level. |
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related to the buoyancy, or the difference |
related to the buoyancy, or the difference |
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between the moist static energy in the cloud and in the environment: |
between the moist static energy in the cloud and in the environment: |
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\[ |
\[ |
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A = \int_{P_D}^{P_B} { {\eta \over {1 + \gamma} } |
A = \int_{P_D}^{P_B} \frac{\eta}{1 + \gamma} |
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\left[ {{h_c-h^*} \over {P^{\kappa}}} \right] dP^{\kappa}} |
\left[ \frac{h_c-h^*}{P^{\kappa}} \right] dP^{\kappa} |
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\] |
\] |
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|
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where $\gamma$ is ${L \over {c_p}}\pp{q^*}{T}$ obtained from the Claussius Clapeyron equation, |
where $\gamma$ is $\frac{L}{c_p}\pp{q^*}{T}$ obtained from the Claussius Clapeyron equation, |
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and the subscript $c$ refers to the value inside the cloud. |
and the subscript $c$ refers to the value inside the cloud. |
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the clouds} is assumed to approximately balance the rate of change of $A$ {\em due to the generation |
the clouds} is assumed to approximately balance the rate of change of $A$ {\em due to the generation |
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by the large scale}. This is the quasi-equilibrium assumption, and results in an expression for $m_B$: |
by the large scale}. This is the quasi-equilibrium assumption, and results in an expression for $m_B$: |
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\[ |
\[ |
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m_B = {{- \left.{dA \over dt} \right|_{ls}} \over K} |
m_B = \frac{- \left. \frac{dA}{dt} \right|_{ls}}{K} |
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\] |
\] |
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where $K$ is the cloud kernel, defined as the rate of change of the cloud work function per |
where $K$ is the cloud kernel, defined as the rate of change of the cloud work function per |
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temperature (through latent heating and compensating subsidence) and moisture (through |
temperature (through latent heating and compensating subsidence) and moisture (through |
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precipitation and detrainment): |
precipitation and detrainment): |
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\[ |
\[ |
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\left.{\pp{\theta}{t}}\right|_{c} = \alpha { m_B \over {c_p P^{\kappa}}} \eta \pp{s}{p} |
\left.{\pp{\theta}{t}}\right|_{c} = \alpha \frac{ m_B}{c_p P^{\kappa}} \eta \pp{s}{p} |
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\] |
\] |
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and |
and |
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\[ |
\[ |
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\left.{\pp{q}{t}}\right|_{c} = \alpha { m_B \over {L}} \eta (\pp{h}{p}-\pp{s}{p}) |
\left.{\pp{q}{t}}\right|_{c} = \alpha \frac{ m_B}{L} \eta (\pp{h}{p}-\pp{s}{p}) |
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\] |
\] |
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where $\theta = {T \over P^{\kappa}}$, $P = (p/p_0)$, and $\alpha$ is the relaxation parameter. |
where $\theta = \frac{T}{P^{\kappa}}$, $P = (p/p_0)$, and $\alpha$ is the relaxation parameter. |
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As an approximation to a full interaction between the different allowable subensembles, |
As an approximation to a full interaction between the different allowable subensembles, |
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many clouds are simulated frequently, each modifying the large scale environment some fraction |
many clouds are simulated frequently, each modifying the large scale environment some fraction |
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towards equillibrium. |
towards equillibrium. |
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In addition to the RAS cumulus convection scheme, the fizhi package employs a |
In addition to the RAS cumulus convection scheme, the fizhi package employs a |
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Kessler-type scheme for the re-evaporation of falling rain (Sud and Molod, 1988), which |
Kessler-type scheme for the re-evaporation of falling rain (\cite{sudm:88}), which |
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correspondingly adjusts the temperature assuming $h$ is conserved. RAS in its current |
correspondingly adjusts the temperature assuming $h$ is conserved. RAS in its current |
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formulation assumes that all cloud water is deposited into the detrainment level as rain. |
formulation assumes that all cloud water is deposited into the detrainment level as rain. |
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All of the rain is available for re-evaporation, which begins in the level below detrainment. |
All of the rain is available for re-evaporation, which begins in the level below detrainment. |
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detrained liquid water amount given by |
detrained liquid water amount given by |
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\[ |
\[ |
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F_{RAS} = \min\left[ {l_{RAS}\over l_c}, 1.0 \right] |
F_{RAS} = \min\left[ \frac{l_{RAS}}{l_c}, 1.0 \right] |
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\] |
\] |
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where $l_c$ is an assigned critical value equal to $1.25$ g/kg. |
where $l_c$ is an assigned critical value equal to $1.25$ g/kg. |
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A memory is associated with convective clouds defined by: |
A memory is associated with convective clouds defined by: |
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\[ |
\[ |
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F_{RAS}^n = \min\left[ F_{RAS} + (1-{\Delta t_{RAS}\over\tau})F_{RAS}^{n-1}, 1.0 \right] |
F_{RAS}^n = \min\left[ F_{RAS} + (1-\frac{\Delta t_{RAS}}{\tau})F_{RAS}^{n-1}, 1.0 \right] |
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\] |
\] |
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where $F_{RAS}$ is the instantanious cloud fraction and $F_{RAS}^{n-1}$ is the cloud fraction |
where $F_{RAS}$ is the instantanious cloud fraction and $F_{RAS}^{n-1}$ is the cloud fraction |
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humidity: |
humidity: |
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\[ |
\[ |
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F_{LS} = \min\left[ { \left( {RH-RH_c \over 1-RH_c} \right) }^2, 1.0 \right] |
F_{LS} = \min\left[ { \left( \frac{RH-RH_c}{1-RH_c} \right) }^2, 1.0 \right] |
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\] |
\] |
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where |
where |
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\bqa |
\bqa |
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RH_c & = & 1-s(1-s)(2-\sqrt{3}+2\sqrt{3} \, s)r \nonumber \\ |
RH_c & = & 1-s(1-s)(2-\sqrt{3}+2\sqrt{3} \, s)r \nonumber \\ |
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s & = & p/p_{surf} \nonumber \\ |
s & = & p/p_{surf} \nonumber \\ |
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r & = & \left( {1.0-RH_{min} \over \alpha} \right) \nonumber \\ |
r & = & \left( \frac{1.0-RH_{min}}{\alpha} \right) \nonumber \\ |
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RH_{min} & = & 0.75 \nonumber \\ |
RH_{min} & = & 0.75 \nonumber \\ |
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\alpha & = & 0.573285 \nonumber . |
\alpha & = & 0.573285 \nonumber . |
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\eqa |
\eqa |
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These cloud fractions are suppressed, however, in regions where the convective |
These cloud fractions are suppressed, however, in regions where the convective |
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sub-cloud layer is conditionally unstable. The functional form of $RH_c$ is shown in |
sub-cloud layer is conditionally unstable. The functional form of $RH_c$ is shown in |
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Figure (\ref{fig:fizhi:rhcrit}). |
Figure (\ref{fig.rhcrit}). |
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\begin{figure*}[htbp] |
\begin{figure*}[htbp] |
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\vspace{0.4in} |
\vspace{0.4in} |
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\centerline{ \epsfysize=4.0in \epsfbox{part6/rhcrit.ps}} |
\centerline{ \epsfysize=4.0in \epsfbox{s_phys_pkgs/figs/rhcrit.ps}} |
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\vspace{0.4in} |
\vspace{0.4in} |
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\caption [Critical Relative Humidity for Clouds.] |
\caption [Critical Relative Humidity for Clouds.] |
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{Critical Relative Humidity for Clouds.} |
{Critical Relative Humidity for Clouds.} |
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\label{fig:fizhi:rhcrit} |
\label{fig.rhcrit} |
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\end{figure*} |
\end{figure*} |
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The total cloud fraction in a grid box is determined by the larger of the two cloud fractions: |
The total cloud fraction in a grid box is determined by the larger of the two cloud fractions: |
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Finally, cloud fractions are time-averaged between calls to the radiation packages. |
Finally, cloud fractions are time-averaged between calls to the radiation packages. |
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\subsubsection{Radiation} |
Radiation: |
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The parameterization of radiative heating in the fizhi package includes effects |
The parameterization of radiative heating in the fizhi package includes effects |
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from both shortwave and longwave processes. |
from both shortwave and longwave processes. |
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and a $CO_2$ mixing ratio of 330 ppm. |
and a $CO_2$ mixing ratio of 330 ppm. |
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For the ozone mixing ratio, monthly mean zonally averaged |
For the ozone mixing ratio, monthly mean zonally averaged |
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climatological values specified as a function |
climatological values specified as a function |
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of latitude and height (Rosenfield, et al., 1987) are linearly interpolated to the current time. |
of latitude and height (\cite{rosen:87}) are linearly interpolated to the current time. |
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\paragraph{Shortwave Radiation} |
\paragraph{Shortwave Radiation} |
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clouds, and aerosols and due to the |
clouds, and aerosols and due to the |
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scattering by clouds, aerosols, and gases. |
scattering by clouds, aerosols, and gases. |
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The shortwave radiative processes are described by |
The shortwave radiative processes are described by |
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Chou (1990,1992). This shortwave package |
\cite{chou:90,chou:92}. This shortwave package |
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uses the Delta-Eddington approximation to compute the |
uses the Delta-Eddington approximation to compute the |
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bulk scattering properties of a single layer following King and Harshvardhan (JAS, 1986). |
bulk scattering properties of a single layer following King and Harshvardhan (JAS, 1986). |
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The transmittance and reflectance of diffuse radiation |
The transmittance and reflectance of diffuse radiation |
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follow the procedures of Sagan and Pollock (JGR, 1967) and Lacis and Hansen (JAS, 1974). |
follow the procedures of Sagan and Pollock (JGR, 1967) and \cite{lhans:74}. |
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Highly accurate heating rate calculations are obtained through the use |
Highly accurate heating rate calculations are obtained through the use |
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of an optimal grouping strategy of spectral bands. By grouping the UV and visible regions |
of an optimal grouping strategy of spectral bands. By grouping the UV and visible regions |
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of a given layer is then scaled for both the direct (as a function of the |
of a given layer is then scaled for both the direct (as a function of the |
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solar zenith angle) and diffuse beam radiation |
solar zenith angle) and diffuse beam radiation |
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so that the grouped layer reflectance is the same as the original reflectance. |
so that the grouped layer reflectance is the same as the original reflectance. |
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The solar flux is computed for each of the eight cloud realizations possible |
The solar flux is computed for each of eight cloud realizations possible within this |
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(see Figure \ref{fig:fizhi:cloud}) within this |
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low/middle/high classification, and appropriately averaged to produce the net solar flux. |
low/middle/high classification, and appropriately averaged to produce the net solar flux. |
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\begin{figure*}[htbp] |
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\vspace{0.4in} |
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\centerline{ \epsfysize=4.0in %\epsfbox{part6/rhcrit.ps} |
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} |
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\vspace{0.4in} |
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\caption {Low-Middle-High Cloud Configurations} |
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\label{fig:fizhi:cloud} |
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\end{figure*} |
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\paragraph{Longwave Radiation} |
\paragraph{Longwave Radiation} |
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The longwave radiation package used in the fizhi package is thoroughly described by Chou and Suarez (1994). |
The longwave radiation package used in the fizhi package is thoroughly described by \cite{chsz:94}. |
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As described in that document, IR fluxes are computed due to absorption by water vapor, carbon |
As described in that document, IR fluxes are computed due to absorption by water vapor, carbon |
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dioxide, and ozone. The spectral bands together with their absorbers and parameterization methods, |
dioxide, and ozone. The spectral bands together with their absorbers and parameterization methods, |
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configured for the fizhi package, are shown in Table \ref{tab:fizhi:longwave}. |
configured for the fizhi package, are shown in Table \ref{tab:fizhi:longwave}. |
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\end{tabular} |
\end{tabular} |
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\end{center} |
\end{center} |
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\vspace{0.1in} |
\vspace{0.1in} |
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\caption{IR Spectral Bands, Absorbers, and Parameterization Method (from Chou and Suarez, 1994)} |
\caption{IR Spectral Bands, Absorbers, and Parameterization Method (from \cite{chsz:94})} |
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\label{tab:fizhi:longwave} |
\label{tab:fizhi:longwave} |
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\end{table} |
\end{table} |
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the large-scale and sub-grid scale optical depths, normalized by the total cloud fraction in the |
the large-scale and sub-grid scale optical depths, normalized by the total cloud fraction in the |
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layer: |
layer: |
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\[ \tau = \left( {F_{RAS} \,\,\, \tau_{RAS} + F_{LS} \,\,\, \tau_{LS} \over F_{RAS}+F_{LS} } \right) \Delta p, \] |
\[ \tau = \left( \frac{F_{RAS} \,\,\, \tau_{RAS} + F_{LS} \,\,\, \tau_{LS} }{ F_{RAS}+F_{LS} } \right) \Delta p, \] |
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|
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where $F_{RAS}$ and $F_{LS}$ are the time-averaged cloud fractions associated with RAS and large-scale |
where $F_{RAS}$ and $F_{LS}$ are the time-averaged cloud fractions associated with RAS and large-scale |
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processes described in Section \ref{sec:fizhi:clouds}. |
processes described in Section \ref{sec:fizhi:clouds}. |
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hours). Therefore, in a time-averaged sense, both convective and large-scale |
hours). Therefore, in a time-averaged sense, both convective and large-scale |
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cloudiness can exist in a given grid-box. |
cloudiness can exist in a given grid-box. |
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\subsubsection{Turbulence} |
\paragraph{Turbulence}: |
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Turbulence is parameterized in the fizhi package to account for its contribution to the |
Turbulence is parameterized in the fizhi package to account for its contribution to the |
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vertical exchange of heat, moisture, and momentum. |
vertical exchange of heat, moisture, and momentum. |
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The turbulence scheme is invoked every 30 minutes, and employs a backward-implicit iterative |
The turbulence scheme is invoked every 30 minutes, and employs a backward-implicit iterative |
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of second turbulent moments is explicitly modeled by representing the third moments in terms of |
of second turbulent moments is explicitly modeled by representing the third moments in terms of |
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the first and second moments. This approach is known as a second-order closure modeling. |
the first and second moments. This approach is known as a second-order closure modeling. |
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To simplify and streamline the computation of the second moments, the level 2.5 assumption |
To simplify and streamline the computation of the second moments, the level 2.5 assumption |
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of Mellor and Yamada (1974) and Yamada (1977) is employed, in which only the turbulent |
of Mellor and Yamada (1974) and \cite{yam:77} is employed, in which only the turbulent |
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kinetic energy (TKE), |
kinetic energy (TKE), |
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\[ {\h}{q^2}={\overline{{u^{\prime}}^2}}+{\overline{{v^{\prime}}^2}}+{\overline{{w^{\prime}}^2}}, \] |
\[ {\h}{q^2}={\overline{{u^{\prime}}^2}}+{\overline{{v^{\prime}}^2}}+{\overline{{w^{\prime}}^2}}, \] |
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and is written: |
and is written: |
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|
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\[ |
\[ |
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{\dd{}{t} ({{\h} q^2})} - { \pp{}{z} ({ {5 \over 3} {{\lambda}_1} q { \pp {}{z} |
{\dd{}{t} ({{\h} q^2})} - { \pp{}{z} ({ \frac{5}{3} {{\lambda}_1} q { \pp {}{z} |
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({\h}q^2)} })} = |
({\h}q^2)} })} = |
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{- \overline{{u^{\prime}}{w^{\prime}}} { \pp{U}{z} }} - {\overline{{v^{\prime}}{w^{\prime}}} |
{- \overline{{u^{\prime}}{w^{\prime}}} { \pp{U}{z} }} - {\overline{{v^{\prime}}{w^{\prime}}} |
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{ \pp{V}{z} }} + {{g \over {\Theta_0}}{\overline{{w^{\prime}}{{{\theta}_v}^{\prime}}}} } |
{ \pp{V}{z} }} + {\frac{g}{\Theta_0}{\overline{{w^{\prime}}{{{\theta}_v}^{\prime}}}} |
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- { q^3 \over {{\Lambda} _1} } |
- \frac{ q^3}{{\Lambda}_1} } |
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\] |
\] |
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|
|
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where $q$ is the turbulent velocity, ${u^{\prime}}$, ${v^{\prime}}$, ${w^{\prime}}$ and |
where $q$ is the turbulent velocity, ${u^{\prime}}$, ${v^{\prime}}$, ${w^{\prime}}$ and |
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|
|
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In the level 2.5 approach, the vertical fluxes of the scalars $\theta_v$ and $q$ and the |
In the level 2.5 approach, the vertical fluxes of the scalars $\theta_v$ and $q$ and the |
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wind components $u$ and $v$ are expressed in terms of the diffusion coefficients $K_h$ and |
wind components $u$ and $v$ are expressed in terms of the diffusion coefficients $K_h$ and |
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$K_m$, respectively. In the statisically realizable level 2.5 turbulence scheme of Helfand |
$K_m$, respectively. In the statisically realizable level 2.5 turbulence scheme of |
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and Labraga (1988), these diffusion coefficients are expressed as |
\cite{helflab:88}, these diffusion coefficients are expressed as |
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|
|
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\[ |
\[ |
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K_h |
K_h |
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= \left\{ \begin{array}{l@{\quad\mbox{for}\quad}l} q \, \ell \, S_H(G_M,G_H) \, & \mbox{decaying turbulence} |
= \left\{ \begin{array}{l@{\quad\mbox{for}\quad}l} q \, \ell \, S_H(G_M,G_H) \, & \mbox{decaying turbulence} |
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\\ { q^2 \over {q_e} } \, \ell \, S_{H}(G_{M_e},G_{H_e}) \, & \mbox{growing turbulence} \end{array} \right. |
\\ \frac{ q^2 }{ q_e } \, \ell \, S_{H}(G_{M_e},G_{H_e}) \, & \mbox{growing turbulence} \end{array} \right. |
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\] |
\] |
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|
|
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and |
and |
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\[ |
\[ |
500 |
K_m |
K_m |
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= \left\{ \begin{array}{l@{\quad\mbox{for}\quad}l} q \, \ell \, S_M(G_M,G_H) \, & \mbox{decaying turbulence} |
= \left\{ \begin{array}{l@{\quad\mbox{for}\quad}l} q \, \ell \, S_M(G_M,G_H) \, & \mbox{decaying turbulence} |
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\\ { q^2 \over {q_e} } \, \ell \, S_{M}(G_{M_e},G_{H_e}) \, & \mbox{growing turbulence} \end{array} \right. |
\\ \frac{ q^2 }{ q_e } \, \ell \, S_{M}(G_{M_e},G_{H_e}) \, & \mbox{growing turbulence} \end{array} \right. |
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\] |
\] |
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|
|
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where the subscript $e$ refers to the value under conditions of local equillibrium |
where the subscript $e$ refers to the value under conditions of local equillibrium |
511 |
are functions of the Richardson number: |
are functions of the Richardson number: |
512 |
|
|
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\[ |
\[ |
514 |
{\bf RI} = { { {g \over \theta_v} \pp {\theta_v}{z} } \over { (\pp{u}{z})^2 + (\pp{v}{z})^2 } } |
{\bf RI} = \frac{ \frac{g}{\theta_v} \pp{\theta_v}{z} }{ (\pp{u}{z})^2 + (\pp{v}{z})^2 } |
515 |
= { {c_p \pp{\theta_v}{z} \pp{P^ \kappa}{z} } \over { (\pp{u}{z})^2 + (\pp{v}{z})^2 } } . |
= \frac{c_p \pp{\theta_v}{z} \pp{P^ \kappa}{z} }{ (\pp{u}{z})^2 + (\pp{v}{z})^2 } . |
516 |
\] |
\] |
517 |
|
|
518 |
Negative values indicate unstable buoyancy and shear, small positive values ($<0.2$) |
Negative values indicate unstable buoyancy and shear, small positive values ($<0.2$) |
519 |
indicate dominantly unstable shear, and large positive values indicate dominantly stable |
indicate dominantly unstable shear, and large positive values indicate dominantly stable |
520 |
stratification. |
stratification. |
521 |
|
|
522 |
Turbulent eddy diffusion coefficients of momentum, heat and moisture in the surface layer, |
Turbulent eddy diffusion coefficients of momentum, heat and moisture in the |
523 |
which corresponds to the lowest GCM level (see \ref{tab:fizhi:sigma}), |
surface layer, which corresponds to the lowest GCM level |
524 |
|
(see {\it --- missing table ---}%\ref{tab:fizhi:sigma} |
525 |
|
), |
526 |
are calculated using stability-dependant functions based on Monin-Obukhov theory: |
are calculated using stability-dependant functions based on Monin-Obukhov theory: |
527 |
\[ |
\[ |
528 |
{K_m} (surface) = C_u \times u_* = C_D W_s |
{K_m} (surface) = C_u \times u_* = C_D W_s |
538 |
$C_u$ is the dimensionless exchange coefficient for momentum from the surface layer |
$C_u$ is the dimensionless exchange coefficient for momentum from the surface layer |
539 |
similarity functions: |
similarity functions: |
540 |
\[ |
\[ |
541 |
{C_u} = {u_* \over W_s} = { k \over \psi_{m} } |
{C_u} = \frac{u_* }{ W_s} = \frac{ k }{ \psi_{m} } |
542 |
\] |
\] |
543 |
where k is the Von Karman constant and $\psi_m$ is the surface layer non-dimensional |
where k is the Von Karman constant and $\psi_m$ is the surface layer non-dimensional |
544 |
wind shear given by |
wind shear given by |
545 |
\[ |
\[ |
546 |
\psi_{m} = {\int_{\zeta_{0}}^{\zeta} {\phi_{m} \over \zeta} d \zeta} . |
\psi_{m} = {\int_{\zeta_{0}}^{\zeta} \frac{\phi_{m} }{ \zeta} d \zeta} . |
547 |
\] |
\] |
548 |
Here $\zeta$ is the non-dimensional stability parameter, and |
Here $\zeta$ is the non-dimensional stability parameter, and |
549 |
$\phi_m$ is the similarity function of $\zeta$ which expresses the stability dependance of |
$\phi_m$ is the similarity function of $\zeta$ which expresses the stability dependance of |
553 |
$C_t$ is the dimensionless exchange coefficient for heat and |
$C_t$ is the dimensionless exchange coefficient for heat and |
554 |
moisture from the surface layer similarity functions: |
moisture from the surface layer similarity functions: |
555 |
\[ |
\[ |
556 |
{C_t} = -{( {\overline{w^{\prime}\theta^{\prime}}}) \over {u_* \Delta \theta }} = |
{C_t} = -\frac{( \overline{w^{\prime}\theta^{\prime}}) }{ u_* \Delta \theta } = |
557 |
-{( {\overline{w^{\prime}q^{\prime}}}) \over {u_* \Delta q }} = |
-\frac{( \overline{w^{\prime}q^{\prime}}) }{ u_* \Delta q } = |
558 |
{ k \over { (\psi_{h} + \psi_{g}) } } |
\frac{ k }{ (\psi_{h} + \psi_{g}) } |
559 |
\] |
\] |
560 |
where $\psi_h$ is the surface layer non-dimensional temperature gradient given by |
where $\psi_h$ is the surface layer non-dimensional temperature gradient given by |
561 |
\[ |
\[ |
562 |
\psi_{h} = {\int_{\zeta_{0}}^{\zeta} {\phi_{h} \over \zeta} d \zeta} . |
\psi_{h} = {\int_{\zeta_{0}}^{\zeta} \frac{\phi_{h} }{ \zeta} d \zeta} . |
563 |
\] |
\] |
564 |
Here $\phi_h$ is the similarity function of $\zeta$, which expresses the stability dependance of |
Here $\phi_h$ is the similarity function of $\zeta$, which expresses the stability dependance of |
565 |
the temperature and moisture gradients, and is specified differently for stable and unstable |
the temperature and moisture gradients, and is specified differently for stable and unstable |
566 |
layers according to Helfand and Schubert, 1995. |
layers according to \cite{helfschu:95}. |
567 |
|
|
568 |
$\psi_g$ is the non-dimensional temperature or moisture gradient in the viscous sublayer, |
$\psi_g$ is the non-dimensional temperature or moisture gradient in the viscous sublayer, |
569 |
which is the mosstly laminar region between the surface and the tops of the roughness |
which is the mosstly laminar region between the surface and the tops of the roughness |
570 |
elements, in which temperature and moisture gradients can be quite large. |
elements, in which temperature and moisture gradients can be quite large. |
571 |
Based on Yaglom and Kader (1974): |
Based on \cite{yagkad:74}: |
572 |
\[ |
\[ |
573 |
\psi_{g} = { 0.55 (Pr^{2/3} - 0.2) \over \nu^{1/2} } |
\psi_{g} = \frac{ 0.55 (Pr^{2/3} - 0.2) }{ \nu^{1/2} } |
574 |
(h_{0}u_{*} - h_{0_{ref}}u_{*_{ref}})^{1/2} |
(h_{0}u_{*} - h_{0_{ref}}u_{*_{ref}})^{1/2} |
575 |
\] |
\] |
576 |
where Pr is the Prandtl number for air, $\nu$ is the molecular viscosity, $z_{0}$ is the |
where Pr is the Prandtl number for air, $\nu$ is the molecular viscosity, $z_{0}$ is the |
579 |
|
|
580 |
The surface roughness length over oceans is is a function of the surface-stress velocity, |
The surface roughness length over oceans is is a function of the surface-stress velocity, |
581 |
\[ |
\[ |
582 |
{z_0} = c_1u^3_* + c_2u^2_* + c_3u_* + c_4 + {c_5 \over {u_*}} |
{z_0} = c_1u^3_* + c_2u^2_* + c_3u_* + c_4 + \frac{c_5 }{ u_*} |
583 |
\] |
\] |
584 |
where the constants are chosen to interpolate between the reciprocal relation of |
where the constants are chosen to interpolate between the reciprocal relation of |
585 |
Kondo(1975) for weak winds, and the piecewise linear relation of Large and Pond(1981) |
\cite{kondo:75} for weak winds, and the piecewise linear relation of \cite{larpond:81} |
586 |
for moderate to large winds. Roughness lengths over land are specified |
for moderate to large winds. Roughness lengths over land are specified |
587 |
from the climatology of Dorman and Sellers (1989). |
from the climatology of \cite{dorsell:89}. |
588 |
|
|
589 |
For an unstable surface layer, the stability functions, chosen to interpolate between the |
For an unstable surface layer, the stability functions, chosen to interpolate between the |
590 |
condition of small values of $\beta$ and the convective limit, are the KEYPS function |
condition of small values of $\beta$ and the convective limit, are the KEYPS function |
591 |
(Panofsky, 1973) for momentum, and its generalization for heat and moisture: |
(\cite{pano:73}) for momentum, and its generalization for heat and moisture: |
592 |
\[ |
\[ |
593 |
{\phi_m}^4 - 18 \zeta {\phi_m}^3 = 1 \hspace{1cm} ; \hspace{1cm} |
{\phi_m}^4 - 18 \zeta {\phi_m}^3 = 1 \hspace{1cm} ; \hspace{1cm} |
594 |
{\phi_h}^2 - 18 \zeta {\phi_h}^3 = 1 \hspace{1cm} . |
{\phi_h}^2 - 18 \zeta {\phi_h}^3 = 1 \hspace{1cm} . |
597 |
speed approaches zero. |
speed approaches zero. |
598 |
|
|
599 |
For a stable surface layer, the stability functions are the observationally |
For a stable surface layer, the stability functions are the observationally |
600 |
based functions of Clarke (1970), slightly modified for |
based functions of \cite{clarke:70}, slightly modified for |
601 |
the momemtum flux: |
the momemtum flux: |
602 |
\[ |
\[ |
603 |
{\phi_m} = { { 1 + 5 {{\zeta}_1} } \over { 1 + 0.00794 {{\zeta}_1} |
{\phi_m} = \frac{ 1 + 5 {{\zeta}_1} }{ 1 + 0.00794 {\zeta}_1 |
604 |
(1+ 5 {{\zeta}_1}) } } \hspace{1cm} ; \hspace{1cm} |
(1+ 5 {\zeta}_1) } \hspace{1cm} ; \hspace{1cm} |
605 |
{\phi_h} = { { 1 + 5 {{\zeta}_1} } \over { 1 + 0.00794 {\zeta} |
{\phi_h} = \frac{ 1 + 5 {{\zeta}_1} }{ 1 + 0.00794 {\zeta} |
606 |
(1+ 5 {{\zeta}_1}) } } . |
(1+ 5 {{\zeta}_1}) } . |
607 |
\] |
\] |
608 |
The moisture flux also depends on a specified evapotranspiration |
The moisture flux also depends on a specified evapotranspiration |
609 |
coefficient, set to unity over oceans and dependant on the climatological ground wetness over |
coefficient, set to unity over oceans and dependant on the climatological ground wetness over |
648 |
|
|
649 |
The heat conduction through sea ice, $Q_{ice}$, is given by |
The heat conduction through sea ice, $Q_{ice}$, is given by |
650 |
\[ |
\[ |
651 |
{Q_{ice}} = {C_{ti} \over {H_i}} (T_i-T_g) |
{Q_{ice}} = \frac{C_{ti} }{ H_i} (T_i-T_g) |
652 |
\] |
\] |
653 |
where $C_{ti}$ is the thermal conductivity of ice, $H_i$ is the ice thickness, assumed to |
where $C_{ti}$ is the thermal conductivity of ice, $H_i$ is the ice thickness, assumed to |
654 |
be $3 \hspace{.1cm} m$ where sea ice is present, $T_i$ is 273 degrees Kelvin, and $T_g$ is the |
be $3 \hspace{.1cm} m$ where sea ice is present, $T_i$ is 273 degrees Kelvin, and $T_g$ is the |
655 |
surface temperature of the ice. |
surface temperature of the ice. |
656 |
|
|
657 |
$C_g$ is the total heat capacity of the ground, obtained by solving a heat diffusion equation |
$C_g$ is the total heat capacity of the ground, obtained by solving a heat diffusion equation |
658 |
for the penetration of the diurnal cycle into the ground (Blackadar, 1977), and is given by: |
for the penetration of the diurnal cycle into the ground (\cite{black:77}), and is given by: |
659 |
\[ |
\[ |
660 |
C_g = \sqrt{ {\lambda C_s \over 2\omega} } = \sqrt{(0.386 + 0.536W + 0.15W^2)2\times10^{-3} |
C_g = \sqrt{ \frac{\lambda C_s }{ 2\omega} } = \sqrt{(0.386 + 0.536W + 0.15W^2)2\times10^{-3} |
661 |
{86400 \over 2 \pi} } \, \, . |
\frac{86400}{2\pi} } \, \, . |
662 |
\] |
\] |
663 |
Here, the thermal conductivity, $\lambda$, is equal to $2\times10^{-3}$ ${ly\over{ sec}} |
Here, the thermal conductivity, $\lambda$, is equal to $2\times10^{-3}$ $\frac{ly}{sec} |
664 |
{cm \over {^oK}}$, |
\frac{cm}{K}$, |
665 |
the angular velocity of the earth, $\omega$, is written as $86400$ $sec/day$ divided |
the angular velocity of the earth, $\omega$, is written as $86400$ $sec/day$ divided |
666 |
by $2 \pi$ $radians/ |
by $2 \pi$ $radians/ |
667 |
day$, and the expression for $C_s$, the heat capacity per unit volume at the surface, |
day$, and the expression for $C_s$, the heat capacity per unit volume at the surface, |
668 |
is a function of the ground wetness, $W$. |
is a function of the ground wetness, $W$. |
669 |
|
|
670 |
\subsubsection{Land Surface Processes} |
Land Surface Processes: |
671 |
|
|
672 |
\paragraph{Surface Type} |
\paragraph{Surface Type} |
673 |
The fizhi package surface Types are designated using the Koster-Suarez (1992) mosaic |
The fizhi package surface Types are designated using the Koster-Suarez (\cite{ks:91,ks:92}) |
674 |
philosophy which allows multiple ``tiles'', or multiple surface types, in any one |
Land Surface Model (LSM) mosaic philosophy which allows multiple ``tiles'', or multiple surface |
675 |
grid cell. The Koster-Suarez Land Surface Model (LSM) surface type classifications |
types, in any one grid cell. The Koster-Suarez LSM surface type classifications |
676 |
are shown in Table \ref{tab:fizhi:surftype}. The surface types and the percent of the grid |
are shown in Table \ref{tab:fizhi:surftype}. The surface types and the percent of the grid |
677 |
cell occupied by any surface type were derived from the surface classification of |
cell occupied by any surface type were derived from the surface classification of |
678 |
Defries and Townshend (1994), and information about the location of permanent |
\cite{deftow:94}, and information about the location of permanent |
679 |
ice was obtained from the classifications of Dorman and Sellers (1989). |
ice was obtained from the classifications of \cite{dorsell:89}. |
680 |
The surface type for the \txt GCM grid is shown in Figure \ref{fig:fizhi:surftype}. |
The surface type map for a $1^\circ$ grid is shown in Figure \ref{fig:fizhi:surftype}. |
681 |
The determination of the land or sea category of surface type was made from NCAR's |
The determination of the land or sea category of surface type was made from NCAR's |
682 |
10 minute by 10 minute Navy topography |
10 minute by 10 minute Navy topography |
683 |
dataset, which includes information about the percentage of water-cover at any point. |
dataset, which includes information about the percentage of water-cover at any point. |
684 |
The data were averaged to the model's \fxf and \txt grid resolutions, |
The data were averaged to the model's grid resolutions, |
685 |
and any grid-box whose averaged water percentage was $\geq 60 \%$ was |
and any grid-box whose averaged water percentage was $\geq 60 \%$ was |
686 |
defined as a water point. The \fxf grid Land-Water designation was further modified |
defined as a water point. The Land-Water designation was further modified |
687 |
subjectively to ensure sufficient representation from small but isolated land and water regions. |
subjectively to ensure sufficient representation from small but isolated land and water regions. |
688 |
|
|
689 |
\begin{table} |
\begin{table} |
707 |
100 & Ocean \\ \hline |
100 & Ocean \\ \hline |
708 |
\end{tabular} |
\end{tabular} |
709 |
\end{center} |
\end{center} |
710 |
\caption{Surface type designations used to compute surface roughness (over land) |
\caption{Surface type designations.} |
|
and surface albedo.} |
|
711 |
\label{tab:fizhi:surftype} |
\label{tab:fizhi:surftype} |
712 |
\end{table} |
\end{table} |
713 |
|
|
|
|
|
714 |
\begin{figure*}[htbp] |
\begin{figure*}[htbp] |
715 |
\centerline{ \epsfysize=7in \epsfbox{part6/surftypes.ps}} |
\centerline{ \epsfysize=4.0in \epsfbox{s_phys_pkgs/figs/surftype.eps}} |
716 |
\vspace{0.3in} |
\vspace{0.2in} |
717 |
\caption {Surface Type Compinations at \txt resolution.} |
\caption {Surface Type Combinations.} |
718 |
\label{fig:fizhi:surftype} |
\label{fig:fizhi:surftype} |
719 |
\end{figure*} |
\end{figure*} |
720 |
|
|
721 |
\begin{figure*}[htbp] |
% \rotatebox{270}{\centerline{ \epsfysize=4in \epsfbox{s_phys_pkgs/figs/surftypes.eps}}} |
722 |
\centerline{ \epsfysize=7in \epsfbox{part6/surftypes.descrip.ps}} |
% \rotatebox{270}{\centerline{ \epsfysize=4in \epsfbox{s_phys_pkgs/figs/surftypes.descrip.eps}}} |
723 |
\vspace{0.3in} |
%\begin{figure*}[htbp] |
724 |
\caption {Surface Type Descriptions.} |
% \centerline{ \epsfysize=4in \epsfbox{s_phys_pkgs/figs/surftypes.descrip.ps}} |
725 |
\label{fig:fizhi:surftype.desc} |
% \vspace{0.3in} |
726 |
\end{figure*} |
% \caption {Surface Type Descriptions.} |
727 |
|
% \label{fig:fizhi:surftype.desc} |
728 |
|
%\end{figure*} |
729 |
|
|
730 |
|
|
731 |
\paragraph{Surface Roughness} |
\paragraph{Surface Roughness} |
732 |
The surface roughness length over oceans is computed iteratively with the wind |
The surface roughness length over oceans is computed iteratively with the wind |
733 |
stress by the surface layer parameterization (Helfand and Schubert, 1991). |
stress by the surface layer parameterization (\cite{helfschu:95}). |
734 |
It employs an interpolation between the functions of Large and Pond (1981) |
It employs an interpolation between the functions of \cite{larpond:81} |
735 |
for high winds and of Kondo (1975) for weak winds. |
for high winds and of \cite{kondo:75} for weak winds. |
736 |
|
|
737 |
|
|
738 |
\paragraph{Albedo} |
\paragraph{Albedo} |
739 |
The surface albedo computation, described in Koster and Suarez (1991), |
The surface albedo computation, described in \cite{ks:91}, |
740 |
employs the ``two stream'' approximation used in Sellers' (1987) Simple Biosphere (SiB) |
employs the ``two stream'' approximation used in Sellers' (1987) Simple Biosphere (SiB) |
741 |
Model which distinguishes between the direct and diffuse albedos in the visible |
Model which distinguishes between the direct and diffuse albedos in the visible |
742 |
and in the near infra-red spectral ranges. The albedos are functions of the observed |
and in the near infra-red spectral ranges. The albedos are functions of the observed |
745 |
Modifications are made to account for the presence of snow, and its depth relative |
Modifications are made to account for the presence of snow, and its depth relative |
746 |
to the height of the vegetation elements. |
to the height of the vegetation elements. |
747 |
|
|
748 |
\subsubsection{Gravity Wave Drag} |
\paragraph{Gravity Wave Drag} |
749 |
The fizhi package employs the gravity wave drag scheme of Zhou et al. (1996). |
|
750 |
|
The fizhi package employs the gravity wave drag scheme of \cite{zhouetal:95}). |
751 |
This scheme is a modified version of Vernekar et al. (1992), |
This scheme is a modified version of Vernekar et al. (1992), |
752 |
which was based on Alpert et al. (1988) and Helfand et al. (1987). |
which was based on Alpert et al. (1988) and Helfand et al. (1987). |
753 |
In this version, the gravity wave stress at the surface is |
In this version, the gravity wave stress at the surface is |
754 |
based on that derived by Pierrehumbert (1986) and is given by: |
based on that derived by Pierrehumbert (1986) and is given by: |
755 |
|
|
756 |
\bq |
\bq |
757 |
|\vec{\tau}_{sfc}| = {\rho U^3\over{N \ell^*}} \left(F_r^2 \over{1+F_r^2}\right) \, \, , |
|\vec{\tau}_{sfc}| = \frac{\rho U^3}{N \ell^*} \left( \frac{F_r^2}{1+F_r^2}\right) \, \, , |
758 |
\eq |
\eq |
759 |
|
|
760 |
where $F_r = N h /U$ is the Froude number, $N$ is the {\em Brunt - V\"{a}is\"{a}l\"{a}} frequency, $U$ is the |
where $F_r = N h /U$ is the Froude number, $N$ is the {\em Brunt - V\"{a}is\"{a}l\"{a}} frequency, $U$ is the |
764 |
escape through the top of the model, although this effect is small for the current 70-level model. |
escape through the top of the model, although this effect is small for the current 70-level model. |
765 |
The subgrid scale standard deviation is defined by $h$, and is not allowed to exceed 400 m. |
The subgrid scale standard deviation is defined by $h$, and is not allowed to exceed 400 m. |
766 |
|
|
767 |
The effects of using this scheme within a GCM are shown in Takacs and Suarez (1996). |
The effects of using this scheme within a GCM are shown in \cite{taksz:96}. |
768 |
Experiments using the gravity wave drag parameterization yielded significant and |
Experiments using the gravity wave drag parameterization yielded significant and |
769 |
beneficial impacts on both the time-mean flow and the transient statistics of the |
beneficial impacts on both the time-mean flow and the transient statistics of the |
770 |
a GCM climatology, and have eliminated most of the worst dynamically driven biases |
a GCM climatology, and have eliminated most of the worst dynamically driven biases |
780 |
convergence (through a reduction in the flux of westerly momentum by transient flow eddies). |
convergence (through a reduction in the flux of westerly momentum by transient flow eddies). |
781 |
|
|
782 |
|
|
783 |
\subsubsection{Boundary Conditions and other Input Data} |
Boundary Conditions and other Input Data: |
784 |
|
|
785 |
Required fields which are not explicitly predicted or diagnosed during model execution must |
Required fields which are not explicitly predicted or diagnosed during model execution must |
786 |
either be prescribed internally or obtained from external data sets. In the fizhi package these |
either be prescribed internally or obtained from external data sets. In the fizhi package these |
788 |
vegetation index, and the radiation-related background levels of: ozone, carbon dioxide, |
vegetation index, and the radiation-related background levels of: ozone, carbon dioxide, |
789 |
and stratospheric moisture. |
and stratospheric moisture. |
790 |
|
|
791 |
Boundary condition data sets are available at the model's \fxf and \txt |
Boundary condition data sets are available at the model's |
792 |
resolutions for either climatological or yearly varying conditions. |
resolutions for either climatological or yearly varying conditions. |
793 |
Any frequency of boundary condition data can be used in the fizhi package; |
Any frequency of boundary condition data can be used in the fizhi package; |
794 |
however, the current selection of data is summarized in Table \ref{tab:fizhi:bcdata}\@. |
however, the current selection of data is summarized in Table \ref{tab:fizhi:bcdata}\@. |
795 |
The time mean values are interpolated during each model timestep to the |
The time mean values are interpolated during each model timestep to the |
796 |
current time. Future model versions will incorporate boundary conditions at |
current time. |
|
higher spatial \mbox{($1^\circ$ x $1^\circ$)} resolutions. |
|
797 |
|
|
798 |
\begin{table}[htb] |
\begin{table}[htb] |
799 |
\begin{center} |
\begin{center} |
820 |
Surface geopotential heights are provided from an averaging of the Navy 10 minute |
Surface geopotential heights are provided from an averaging of the Navy 10 minute |
821 |
by 10 minute dataset supplied by the National Center for Atmospheric Research (NCAR) to the |
by 10 minute dataset supplied by the National Center for Atmospheric Research (NCAR) to the |
822 |
model's grid resolution. The original topography is first rotated to the proper grid-orientation |
model's grid resolution. The original topography is first rotated to the proper grid-orientation |
823 |
which is being run, and then |
which is being run, and then averages the data to the model resolution. |
|
averages the data to the model resolution. |
|
|
The averaged topography is then passed through a Lanczos (1966) filter in both dimensions |
|
|
which removes the smallest |
|
|
scales while inhibiting Gibbs phenomena. |
|
|
|
|
|
In one dimension, we may define a cyclic function in $x$ as: |
|
|
\begin{equation} |
|
|
f(x) = {a_0 \over 2} + \sum_{k=1}^N \left( a_k \cos(kx) + b_k \sin(kx) \right) |
|
|
\label{eq:fizhi:filt} |
|
|
\end{equation} |
|
|
where $N = { {\rm IM} \over 2 }$ and ${\rm IM}$ is the total number of points in the $x$ direction. |
|
|
Defining $\Delta x = { 2 \pi \over {\rm IM}}$, we may define the average of $f(x)$ over a |
|
|
$2 \Delta x$ region as: |
|
|
|
|
|
\begin{equation} |
|
|
\overline {f(x)} = {1 \over {2 \Delta x}} \int_{x-\Delta x}^{x+\Delta x} f(x^{\prime}) dx^{\prime} |
|
|
\label{eq:fizhi:fave1} |
|
|
\end{equation} |
|
|
|
|
|
Using equation (\ref{eq:fizhi:filt}) in equation (\ref{eq:fizhi:fave1}) and integrating, we may write: |
|
|
|
|
|
\begin{equation} |
|
|
\overline {f(x)} = {a_0 \over 2} + {1 \over {2 \Delta x}} |
|
|
\sum_{k=1}^N \left [ |
|
|
\left. a_k { \sin(kx^{\prime}) \over k } \right /_{x-\Delta x}^{x+\Delta x} - |
|
|
\left. b_k { \cos(kx^{\prime}) \over k } \right /_{x-\Delta x}^{x+\Delta x} |
|
|
\right] |
|
|
\end{equation} |
|
|
or |
|
|
|
|
|
\begin{equation} |
|
|
\overline {f(x)} = {a_0 \over 2} + \sum_{k=1}^N {\sin(k \Delta x) \over {k \Delta x}} |
|
|
\left( a_k \cos(kx) + b_k \sin(kx) \right) |
|
|
\label{eq:fizhi:fave2} |
|
|
\end{equation} |
|
|
|
|
|
Thus, the Fourier wave amplitudes are simply modified by the Lanczos filter response |
|
|
function ${\sin(k\Delta x) \over {k \Delta x}}$. This may be compared with an $mth$-order |
|
|
Shapiro (1970) filter response function, defined as $1-\sin^m({k \Delta x \over 2})$, |
|
|
shown in Figure \ref{fig:fizhi:lanczos}. |
|
|
It should be noted that negative values in the topography resulting from |
|
|
the filtering procedure are {\em not} filled. |
|
|
|
|
|
\begin{figure*}[htbp] |
|
|
\centerline{ \epsfysize=7.0in \epsfbox{part6/lanczos.ps}} |
|
|
\caption{ \label{fig:fizhi:lanczos} Comparison between the Lanczos and $mth$-order Shapiro filter |
|
|
response functions for $m$ = 2, 4, and 8. } |
|
|
\end{figure*} |
|
824 |
|
|
825 |
The standard deviation of the subgrid-scale topography |
The standard deviation of the subgrid-scale topography is computed by interpolating the 10 minute |
826 |
is computed from a modified version of the the Navy 10 minute by 10 minute dataset. |
data to the model's resolution and re-interpolating back to the 10 minute by 10 minute resolution. |
|
The 10 minute by 10 minute topography is passed through a wavelet |
|
|
filter in both dimensions which removes the scale smaller than 20 minutes. |
|
|
The topography is then averaged to $1^\circ x 1^\circ$ grid resolution, and then |
|
|
re-interpolated back to the 10 minute by 10 minute resolution. |
|
827 |
The sub-grid scale variance is constructed based on this smoothed dataset. |
The sub-grid scale variance is constructed based on this smoothed dataset. |
828 |
|
|
829 |
|
|
830 |
\paragraph{Upper Level Moisture} |
\paragraph{Upper Level Moisture} |
831 |
The fizhi package uses climatological water vapor data above 100 mb from the Stratospheric Aerosol and Gas |
The fizhi package uses climatological water vapor data above 100 mb from the Stratospheric Aerosol and Gas |
832 |
Experiment (SAGE) as input into the model's radiation packages. The SAGE data is archived |
Experiment (SAGE) as input into the model's radiation packages. The SAGE data is archived |
833 |
as monthly zonal means at 5$^\circ$ latitudinal resolution. The data is interpolated to the |
as monthly zonal means at $5^\circ$ latitudinal resolution. The data is interpolated to the |
834 |
model's grid location and current time, and blended with the GCM's moisture data. Below 300 mb, |
model's grid location and current time, and blended with the GCM's moisture data. Below 300 mb, |
835 |
the model's moisture data is used. Above 100 mb, the SAGE data is used. Between 100 and 300 mb, |
the model's moisture data is used. Above 100 mb, the SAGE data is used. Between 100 and 300 mb, |
836 |
a linear interpolation (in pressure) is performed using the data from SAGE and the GCM. |
a linear interpolation (in pressure) is performed using the data from SAGE and the GCM. |
837 |
|
|
838 |
|
|
839 |
\subsection{Fizhi Diagnostics} |
\subsubsection{Fizhi Diagnostics} |
840 |
|
|
841 |
\subsubsection{Fizhi Diagnostic Menu} |
Fizhi Diagnostic Menu: |
842 |
\label{sec:fizhi-diagnostics:menu} |
\label{sec:pkg:fizhi:diagnostics} |
843 |
|
|
844 |
\begin{tabular}{llll} |
\begin{tabular}{llll} |
845 |
\hline\hline |
\hline\hline |
1367 |
|
|
1368 |
\newpage |
\newpage |
1369 |
|
|
1370 |
\subsubsection{Fizhi Diagnostic Description} |
Fizhi Diagnostic Description: |
1371 |
|
|
1372 |
In this section we list and describe the diagnostic quantities available within the |
In this section we list and describe the diagnostic quantities available within the |
1373 |
GCM. The diagnostics are listed in the order that they appear in the |
GCM. The diagnostics are listed in the order that they appear in the |
1374 |
Diagnostic Menu, Section \ref{sec:fizhi-diagnostics:menu}. |
Diagnostic Menu, Section \ref{sec:pkg:fizhi:diagnostics}. |
1375 |
In all cases, each diagnostic as currently archived on the output datasets |
In all cases, each diagnostic as currently archived on the output datasets |
1376 |
is time-averaged over its diagnostic output frequency: |
is time-averaged over its diagnostic output frequency: |
1377 |
|
|
1378 |
\[ |
\[ |
1379 |
{\bf DIAGNOSTIC} = {1 \over TTOT} \sum_{t=1}^{t=TTOT} diag(t) |
{\bf DIAGNOSTIC} = \frac{1}{TTOT} \sum_{t=1}^{t=TTOT} diag(t) |
1380 |
\] |
\] |
1381 |
where $TTOT = {{\bf NQDIAG} \over \Delta t}$, {\bf NQDIAG} is the |
where $TTOT = \frac{ {\bf NQDIAG} }{\Delta t}$, {\bf NQDIAG} is the |
1382 |
output frequency of the diagnostic, and $\Delta t$ is |
output frequency of the diagnostic, and $\Delta t$ is |
1383 |
the timestep over which the diagnostic is updated. |
the timestep over which the diagnostic is updated. |
1384 |
|
|
1450 |
through sea ice represents an additional energy source term for the ground temperature equation. |
through sea ice represents an additional energy source term for the ground temperature equation. |
1451 |
|
|
1452 |
\[ |
\[ |
1453 |
{\bf QICE} = {C_{ti} \over {H_i}} (T_i-T_g) |
{\bf QICE} = \frac{C_{ti}}{H_i} (T_i-T_g) |
1454 |
\] |
\] |
1455 |
|
|
1456 |
where $C_{ti}$ is the thermal conductivity of ice, $H_i$ is the ice thickness, assumed to |
where $C_{ti}$ is the thermal conductivity of ice, $H_i$ is the ice thickness, assumed to |
1492 |
\noindent |
\noindent |
1493 |
The non-dimensional stability indicator is the ratio of the buoyancy to the shear: |
The non-dimensional stability indicator is the ratio of the buoyancy to the shear: |
1494 |
\[ |
\[ |
1495 |
{\bf RI} = { { {g \over \theta_v} \pp {\theta_v}{z} } \over { (\pp{u}{z})^2 + (\pp{v}{z})^2 } } |
{\bf RI} = \frac{ \frac{g}{\theta_v} \pp {\theta_v}{z} }{ (\pp{u}{z})^2 + (\pp{v}{z})^2 } |
1496 |
= { {c_p \pp{\theta_v}{z} \pp{P^ \kappa}{z} } \over { (\pp{u}{z})^2 + (\pp{v}{z})^2 } } |
= \frac{c_p \pp{\theta_v}{z} \pp{P^ \kappa}{z} }{ (\pp{u}{z})^2 + (\pp{v}{z})^2 } |
1497 |
\] |
\] |
1498 |
\\ |
\\ |
1499 |
where we used the hydrostatic equation: |
where we used the hydrostatic equation: |
1512 |
The surface exchange coefficient is obtained from the similarity functions for the stability |
The surface exchange coefficient is obtained from the similarity functions for the stability |
1513 |
dependant flux profile relationships: |
dependant flux profile relationships: |
1514 |
\[ |
\[ |
1515 |
{\bf CT} = -{( {\overline{w^{\prime}\theta^{\prime}}}) \over {u_* \Delta \theta }} = |
{\bf CT} = -\frac{( \overline{w^{\prime}\theta^{\prime}} ) }{ u_* \Delta \theta } = |
1516 |
-{( {\overline{w^{\prime}q^{\prime}}}) \over {u_* \Delta q }} = |
-\frac{( \overline{w^{\prime}q^{\prime}} ) }{ u_* \Delta q } = |
1517 |
{ k \over { (\psi_{h} + \psi_{g}) } } |
\frac{ k }{ (\psi_{h} + \psi_{g}) } |
1518 |
\] |
\] |
1519 |
where $\psi_h$ is the surface layer non-dimensional temperature change and $\psi_g$ is the |
where $\psi_h$ is the surface layer non-dimensional temperature change and $\psi_g$ is the |
1520 |
viscous sublayer non-dimensional temperature or moisture change: |
viscous sublayer non-dimensional temperature or moisture change: |
1521 |
\[ |
\[ |
1522 |
\psi_{h} = {\int_{\zeta_{0}}^{\zeta} {\phi_{h} \over \zeta} d \zeta} \hspace{1cm} and |
\psi_{h} = \int_{\zeta_{0}}^{\zeta} \frac{\phi_{h} }{ \zeta} d \zeta \hspace{1cm} and |
1523 |
\hspace{1cm} \psi_{g} = { 0.55 (Pr^{2/3} - 0.2) \over \nu^{1/2} } |
\hspace{1cm} \psi_{g} = \frac{ 0.55 (Pr^{2/3} - 0.2) }{ \nu^{1/2} } |
1524 |
(h_{0}u_{*} - h_{0_{ref}}u_{*_{ref}})^{1/2} |
(h_{0}u_{*} - h_{0_{ref}}u_{*_{ref}})^{1/2} |
1525 |
\] |
\] |
1526 |
and: |
and: |
1529 |
\noindent |
\noindent |
1530 |
$\phi_h$ is the similarity function of $\zeta$, which expresses the stability dependance of |
$\phi_h$ is the similarity function of $\zeta$, which expresses the stability dependance of |
1531 |
the temperature and moisture gradients, specified differently for stable and unstable |
the temperature and moisture gradients, specified differently for stable and unstable |
1532 |
layers according to Helfand and Schubert, 1993. k is the Von Karman constant, $\zeta$ is the |
layers according to \cite{helfschu:95}. k is the Von Karman constant, $\zeta$ is the |
1533 |
non-dimensional stability parameter, Pr is the Prandtl number for air, $\nu$ is the molecular |
non-dimensional stability parameter, Pr is the Prandtl number for air, $\nu$ is the molecular |
1534 |
viscosity, $z_{0}$ is the surface roughness length, $u_*$ is the surface stress velocity |
viscosity, $z_{0}$ is the surface roughness length, $u_*$ is the surface stress velocity |
1535 |
(see diagnostic number 67), and the subscript ref refers to a reference value. |
(see diagnostic number 67), and the subscript ref refers to a reference value. |
1542 |
The surface exchange coefficient is obtained from the similarity functions for the stability |
The surface exchange coefficient is obtained from the similarity functions for the stability |
1543 |
dependant flux profile relationships: |
dependant flux profile relationships: |
1544 |
\[ |
\[ |
1545 |
{\bf CU} = {u_* \over W_s} = { k \over \psi_{m} } |
{\bf CU} = \frac{u_* }{ W_s} = \frac{ k }{ \psi_{m} } |
1546 |
\] |
\] |
1547 |
where $\psi_m$ is the surface layer non-dimensional wind shear: |
where $\psi_m$ is the surface layer non-dimensional wind shear: |
1548 |
\[ |
\[ |
1549 |
\psi_{m} = {\int_{\zeta_{0}}^{\zeta} {\phi_{m} \over \zeta} d \zeta} |
\psi_{m} = {\int_{\zeta_{0}}^{\zeta} \frac{\phi_{m} }{ \zeta} d \zeta} |
1550 |
\] |
\] |
1551 |
\noindent |
\noindent |
1552 |
$\phi_m$ is the similarity function of $\zeta$, which expresses the stability dependance of |
$\phi_m$ is the similarity function of $\zeta$, which expresses the stability dependance of |
1553 |
the temperature and moisture gradients, specified differently for stable and unstable layers |
the temperature and moisture gradients, specified differently for stable and unstable layers |
1554 |
according to Helfand and Schubert, 1993. k is the Von Karman constant, $\zeta$ is the |
according to \cite{helfschu:95}. k is the Von Karman constant, $\zeta$ is the |
1555 |
non-dimensional stability parameter, $u_*$ is the surface stress velocity |
non-dimensional stability parameter, $u_*$ is the surface stress velocity |
1556 |
(see diagnostic number 67), and $W_s$ is the magnitude of the surface layer wind. |
(see diagnostic number 67), and $W_s$ is the magnitude of the surface layer wind. |
1557 |
\\ |
\\ |
1563 |
In the level 2.5 version of the Mellor-Yamada (1974) hierarchy, the turbulent heat or |
In the level 2.5 version of the Mellor-Yamada (1974) hierarchy, the turbulent heat or |
1564 |
moisture flux for the atmosphere above the surface layer can be expressed as a turbulent |
moisture flux for the atmosphere above the surface layer can be expressed as a turbulent |
1565 |
diffusion coefficient $K_h$ times the negative of the gradient of potential temperature |
diffusion coefficient $K_h$ times the negative of the gradient of potential temperature |
1566 |
or moisture. In the Helfand and Labraga (1988) adaptation of this closure, $K_h$ |
or moisture. In the \cite{helflab:88} adaptation of this closure, $K_h$ |
1567 |
takes the form: |
takes the form: |
1568 |
\[ |
\[ |
1569 |
{\bf ET} = K_h = -{( {\overline{w^{\prime}\theta_v^{\prime}}}) \over {\pp{\theta_v}{z}} } |
{\bf ET} = K_h = -\frac{( \overline{w^{\prime}\theta_v^{\prime}}) }{ \pp{\theta_v}{z} } |
1570 |
= \left\{ \begin{array}{l@{\quad\mbox{for}\quad}l} q \, \ell \, S_H(G_M,G_H) & \mbox{decaying turbulence} |
= \left\{ \begin{array}{l@{\quad\mbox{for}\quad}l} q \, \ell \, S_H(G_M,G_H) & \mbox{decaying turbulence} |
1571 |
\\ { q^2 \over {q_e} } \, \ell \, S_{H}(G_{M_e},G_{H_e}) & \mbox{growing turbulence} \end{array} \right. |
\\ \frac{ q^2 }{ q_e } \, \ell \, S_{H}(G_{M_e},G_{H_e}) & \mbox{growing turbulence} \end{array} \right. |
1572 |
\] |
\] |
1573 |
where $q$ is the turbulent velocity, or $\sqrt{2*turbulent \hspace{.2cm} kinetic \hspace{.2cm} |
where $q$ is the turbulent velocity, or $\sqrt{2*turbulent \hspace{.2cm} kinetic \hspace{.2cm} |
1574 |
energy}$, $q_e$ is the turbulence velocity derived from the more simple level 2.0 model, |
energy}$, $q_e$ is the turbulence velocity derived from the more simple level 2.0 model, |
1582 |
|
|
1583 |
\noindent |
\noindent |
1584 |
For the detailed equations and derivations of the modified level 2.5 closure scheme, |
For the detailed equations and derivations of the modified level 2.5 closure scheme, |
1585 |
see Helfand and Labraga, 1988. |
see \cite{helflab:88}. |
1586 |
|
|
1587 |
\noindent |
\noindent |
1588 |
In the surface layer, ${\bf {ET}}$ is the exchange coefficient for heat and moisture, |
In the surface layer, ${\bf {ET}}$ is the exchange coefficient for heat and moisture, |
1604 |
In the level 2.5 version of the Mellor-Yamada (1974) hierarchy, the turbulent heat |
In the level 2.5 version of the Mellor-Yamada (1974) hierarchy, the turbulent heat |
1605 |
momentum flux for the atmosphere above the surface layer can be expressed as a turbulent |
momentum flux for the atmosphere above the surface layer can be expressed as a turbulent |
1606 |
diffusion coefficient $K_m$ times the negative of the gradient of the u-wind. |
diffusion coefficient $K_m$ times the negative of the gradient of the u-wind. |
1607 |
In the Helfand and Labraga (1988) adaptation of this closure, $K_m$ |
In the \cite{helflab:88} adaptation of this closure, $K_m$ |
1608 |
takes the form: |
takes the form: |
1609 |
\[ |
\[ |
1610 |
{\bf EU} = K_m = -{( {\overline{u^{\prime}w^{\prime}}}) \over {\pp{U}{z}} } |
{\bf EU} = K_m = -\frac{( \overline{u^{\prime}w^{\prime}} ) }{ \pp{U}{z} } |
1611 |
= \left\{ \begin{array}{l@{\quad\mbox{for}\quad}l} q \, \ell \, S_M(G_M,G_H) & \mbox{decaying turbulence} |
= \left\{ \begin{array}{l@{\quad\mbox{for}\quad}l} q \, \ell \, S_M(G_M,G_H) & \mbox{decaying turbulence} |
1612 |
\\ { q^2 \over {q_e} } \, \ell \, S_{M}(G_{M_e},G_{H_e}) & \mbox{growing turbulence} \end{array} \right. |
\\ \frac{ q^2 }{ q_e } \, \ell \, S_{M}(G_{M_e},G_{H_e}) & \mbox{growing turbulence} \end{array} \right. |
1613 |
\] |
\] |
1614 |
\noindent |
\noindent |
1615 |
where $q$ is the turbulent velocity, or $\sqrt{2*turbulent \hspace{.2cm} kinetic \hspace{.2cm} |
where $q$ is the turbulent velocity, or $\sqrt{2*turbulent \hspace{.2cm} kinetic \hspace{.2cm} |
1624 |
|
|
1625 |
\noindent |
\noindent |
1626 |
For the detailed equations and derivations of the modified level 2.5 closure scheme, |
For the detailed equations and derivations of the modified level 2.5 closure scheme, |
1627 |
see Helfand and Labraga, 1988. |
see \cite{helflab:88}. |
1628 |
|
|
1629 |
\noindent |
\noindent |
1630 |
In the surface layer, ${\bf {EU}}$ is the exchange coefficient for momentum, |
In the surface layer, ${\bf {EU}}$ is the exchange coefficient for momentum, |
1712 |
\] |
\] |
1713 |
where: |
where: |
1714 |
\[ |
\[ |
1715 |
\left.{\pp{T}{t}}\right|_{c} = R \sum_i \left( \alpha { m_B \over c_p} \Gamma_s \right)_i |
\left.{\pp{T}{t}}\right|_{c} = R \sum_i \left( \alpha \frac{m_B}{c_p} \Gamma_s \right)_i |
1716 |
\hspace{.4cm} and |
\hspace{.4cm} and |
1717 |
\hspace{.4cm} \left.{\pp{T}{t}}\right|_{ls} = {L \over c_p } (q^*-q) |
\hspace{.4cm} \left.{\pp{T}{t}}\right|_{ls} = \frac{L}{c_p} (q^*-q) |
1718 |
\] |
\] |
1719 |
and |
and |
1720 |
\[ |
\[ |
1742 |
\] |
\] |
1743 |
where: |
where: |
1744 |
\[ |
\[ |
1745 |
\left.{\pp{q}{t}}\right|_{c} = R \sum_i \left( \alpha { m_B \over {L}}(\Gamma_h-\Gamma_s) \right)_i |
\left.{\pp{q}{t}}\right|_{c} = R \sum_i \left( \alpha \frac{m_B}{L}(\Gamma_h-\Gamma_s) \right)_i |
1746 |
\hspace{.4cm} and |
\hspace{.4cm} and |
1747 |
\hspace{.4cm} \left.{\pp{q}{t}}\right|_{ls} = (q^*-q) |
\hspace{.4cm} \left.{\pp{q}{t}}\right|_{ls} = (q^*-q) |
1748 |
\] |
\] |
1788 |
Finally, the net longwave heating rate is calculated as the vertical divergence of the |
Finally, the net longwave heating rate is calculated as the vertical divergence of the |
1789 |
net terrestrial radiative fluxes: |
net terrestrial radiative fluxes: |
1790 |
\[ |
\[ |
1791 |
\pp{\rho c_p T}{t} = - {\partial \over \partial z} F_{LW}^{NET} , |
\pp{\rho c_p T}{t} = - \p{z} F_{LW}^{NET} , |
1792 |
\] |
\] |
1793 |
or |
or |
1794 |
\[ |
\[ |
1795 |
{\bf RADLW} = \frac{g}{c_p \pi} {\partial \over \partial \sigma} F_{LW}^{NET} . |
{\bf RADLW} = \frac{g}{c_p \pi} \p{\sigma} F_{LW}^{NET} . |
1796 |
\] |
\] |
1797 |
|
|
1798 |
\noindent |
\noindent |
1823 |
\noindent |
\noindent |
1824 |
The heating rate due to Shortwave Radiation under cloudy skies is defined as: |
The heating rate due to Shortwave Radiation under cloudy skies is defined as: |
1825 |
\[ |
\[ |
1826 |
\pp{\rho c_p T}{t} = - {\partial \over \partial z} F(cloudy)_{SW}^{NET} \cdot {\rm RADSWT}, |
\pp{\rho c_p T}{t} = - \p{z} F(cloudy)_{SW}^{NET} \cdot {\rm RADSWT}, |
1827 |
\] |
\] |
1828 |
or |
or |
1829 |
\[ |
\[ |
1830 |
{\bf RADSW} = \frac{g}{c_p \pi} {\partial \over \partial \sigma} F(cloudy)_{SW}^{NET}\cdot {\rm RADSWT} . |
{\bf RADSW} = \frac{g}{c_p \pi} \p{\sigma} F(cloudy)_{SW}^{NET}\cdot {\rm RADSWT} . |
1831 |
\] |
\] |
1832 |
|
|
1833 |
\noindent |
\noindent |
1847 |
the vertical integral or total precipitable amount is given by: |
the vertical integral or total precipitable amount is given by: |
1848 |
\[ |
\[ |
1849 |
{\bf PREACC} = \int_{surf}^{top} \rho \Delta q_{moist} dz = - \int_{surf}^{top} \Delta q_{moist} |
{\bf PREACC} = \int_{surf}^{top} \rho \Delta q_{moist} dz = - \int_{surf}^{top} \Delta q_{moist} |
1850 |
{dp \over g} = {1 \over g} \int_0^1 \Delta q_{moist} dp |
\frac{dp}{g} = \frac{1}{g} \int_0^1 \Delta q_{moist} dp |
1851 |
\] |
\] |
1852 |
\\ |
\\ |
1853 |
|
|
1864 |
the vertical integral or total precipitable amount is given by: |
the vertical integral or total precipitable amount is given by: |
1865 |
\[ |
\[ |
1866 |
{\bf PRECON} = \int_{surf}^{top} \rho \Delta q_{cum} dz = - \int_{surf}^{top} \Delta q_{cum} |
{\bf PRECON} = \int_{surf}^{top} \rho \Delta q_{cum} dz = - \int_{surf}^{top} \Delta q_{cum} |
1867 |
{dp \over g} = {1 \over g} \int_0^1 \Delta q_{cum} dp |
\frac{dp}{g} = \frac{1}{g} \int_0^1 \Delta q_{cum} dp |
1868 |
\] |
\] |
1869 |
\\ |
\\ |
1870 |
|
|
1949 |
\noindent |
\noindent |
1950 |
The drag coefficient for momentum obtained by assuming a neutrally stable surface layer: |
The drag coefficient for momentum obtained by assuming a neutrally stable surface layer: |
1951 |
\[ |
\[ |
1952 |
{\bf CN} = { k \over { \ln({h \over {z_0}})} } |
{\bf CN} = \frac{ k }{ \ln(\frac{h }{z_0}) } |
1953 |
\] |
\] |
1954 |
|
|
1955 |
\noindent |
\noindent |
1985 |
\noindent |
\noindent |
1986 |
where |
where |
1987 |
\[ |
\[ |
1988 |
\theta_{v{Nrphys+1}} = { T_g \over {P^{\kappa}_{surf}} } (1 + .609 q_{Nrphys+1}) \hspace{1cm} |
\theta_{v{Nrphys+1}} = \frac{ T_g }{ P^{\kappa}_{surf} } (1 + .609 q_{Nrphys+1}) \hspace{1cm} |
1989 |
and \hspace{1cm} q_{Nrphys+1} = q_{Nrphys} + \beta(q^*(T_g,P_s) - q_{Nrphys}) |
and \hspace{1cm} q_{Nrphys+1} = q_{Nrphys} + \beta(q^*(T_g,P_s) - q_{Nrphys}) |
1990 |
\] |
\] |
1991 |
|
|
2014 |
sea ice, $H$ is the upward sensible heat flux, $LE$ is the upward latent heat |
sea ice, $H$ is the upward sensible heat flux, $LE$ is the upward latent heat |
2015 |
flux, and $C_g$ is the total heat capacity of the ground. |
flux, and $C_g$ is the total heat capacity of the ground. |
2016 |
$C_g$ is obtained by solving a heat diffusion equation |
$C_g$ is obtained by solving a heat diffusion equation |
2017 |
for the penetration of the diurnal cycle into the ground (Blackadar, 1977), and is given by: |
for the penetration of the diurnal cycle into the ground (\cite{black:77}), and is given by: |
2018 |
\[ |
\[ |
2019 |
C_g = \sqrt{ {\lambda C_s \over {2 \omega} } } = \sqrt{(0.386 + 0.536W + 0.15W^2)2x10^{-3} |
C_g = \sqrt{ \frac{\lambda C_s }{ 2 \omega } } = \sqrt{(0.386 + 0.536W + 0.15W^2)2x10^{-3} |
2020 |
{ 86400. \over {2 \pi} } } \, \, . |
\frac{86400.}{2\pi} } \, \, . |
2021 |
\] |
\] |
2022 |
\noindent |
\noindent |
2023 |
Here, the thermal conductivity, $\lambda$, is equal to $2x10^{-3}$ ${ly\over{ sec}} |
Here, the thermal conductivity, $\lambda$, is equal to $2x10^{-3}$ $\frac{ly}{sec} |
2024 |
{cm \over {^oK}}$, |
\frac{cm}{K}$, |
2025 |
the angular velocity of the earth, $\omega$, is written as $86400$ $sec/day$ divided |
the angular velocity of the earth, $\omega$, is written as $86400$ $sec/day$ divided |
2026 |
by $2 \pi$ $radians/ |
by $2 \pi$ $radians/ |
2027 |
day$, and the expression for $C_s$, the heat capacity per unit volume at the surface, |
day$, and the expression for $C_s$, the heat capacity per unit volume at the surface, |
2163 |
vertical divergence of the |
vertical divergence of the |
2164 |
clear-sky longwave radiative flux: |
clear-sky longwave radiative flux: |
2165 |
\[ |
\[ |
2166 |
\pp{\rho c_p T}{t}_{clearsky} = - {\partial \over \partial z} F(clearsky)_{LW}^{NET} , |
\pp{\rho c_p T}{t}_{clearsky} = - \p{z} F(clearsky)_{LW}^{NET} , |
2167 |
\] |
\] |
2168 |
or |
or |
2169 |
\[ |
\[ |
2170 |
{\bf LWCLR} = \frac{g}{c_p \pi} {\partial \over \partial \sigma} F(clearsky)_{LW}^{NET} . |
{\bf LWCLR} = \frac{g}{c_p \pi} \p{\sigma} F(clearsky)_{LW}^{NET} . |
2171 |
\] |
\] |
2172 |
|
|
2173 |
\noindent |
\noindent |
2357 |
the surface layer top impeded by the surface drag: |
the surface layer top impeded by the surface drag: |
2358 |
\[ |
\[ |
2359 |
{\bf USTAR} = C_uW_s \hspace{1cm}where: \hspace{.2cm} |
{\bf USTAR} = C_uW_s \hspace{1cm}where: \hspace{.2cm} |
2360 |
C_u = {k \over {\psi_m} } |
C_u = \frac{k}{\psi_m} |
2361 |
\] |
\] |
2362 |
|
|
2363 |
\noindent |
\noindent |
2369 |
|
|
2370 |
\noindent |
\noindent |
2371 |
Over the land surface, the surface roughness length is interpolated to the local |
Over the land surface, the surface roughness length is interpolated to the local |
2372 |
time from the monthly mean data of Dorman and Sellers (1989). Over the ocean, |
time from the monthly mean data of \cite{dorsell:89}. Over the ocean, |
2373 |
the roughness length is a function of the surface-stress velocity, $u_*$. |
the roughness length is a function of the surface-stress velocity, $u_*$. |
2374 |
\[ |
\[ |
2375 |
{\bf Z0} = c_1u^3_* + c_2u^2_* + c_3u_* + c_4 + {c_5 \over {u_*}} |
{\bf Z0} = c_1u^3_* + c_2u^2_* + c_3u_* + c_4 + {c_5}{u_*} |
2376 |
\] |
\] |
2377 |
|
|
2378 |
\noindent |
\noindent |
2379 |
where the constants are chosen to interpolate between the reciprocal relation of |
where the constants are chosen to interpolate between the reciprocal relation of |
2380 |
Kondo(1975) for weak winds, and the piecewise linear relation of Large and Pond(1981) |
\cite{kondo:75} for weak winds, and the piecewise linear relation of \cite{larpond:81} |
2381 |
for moderate to large winds. |
for moderate to large winds. |
2382 |
\\ |
\\ |
2383 |
|
|
2426 |
\noindent |
\noindent |
2427 |
The heating rate due to Shortwave Radiation under clear skies is defined as: |
The heating rate due to Shortwave Radiation under clear skies is defined as: |
2428 |
\[ |
\[ |
2429 |
\pp{\rho c_p T}{t} = - {\partial \over \partial z} F(clear)_{SW}^{NET} \cdot {\rm RADSWT}, |
\pp{\rho c_p T}{t} = - \p{z} F(clear)_{SW}^{NET} \cdot {\rm RADSWT}, |
2430 |
\] |
\] |
2431 |
or |
or |
2432 |
\[ |
\[ |
2433 |
{\bf SWCLR} = \frac{g}{c_p } {\partial \over \partial p} F(clear)_{SW}^{NET}\cdot {\rm RADSWT} . |
{\bf SWCLR} = \frac{g}{c_p } \p{p} F(clear)_{SW}^{NET}\cdot {\rm RADSWT} . |
2434 |
\] |
\] |
2435 |
|
|
2436 |
\noindent |
\noindent |
2617 |
\end{eqnarray*} |
\end{eqnarray*} |
2618 |
then, since there are no surface pressure changes due to Diabatic processes, we may write |
then, since there are no surface pressure changes due to Diabatic processes, we may write |
2619 |
\[ |
\[ |
2620 |
\pp{T}{t}_{Diabatic} = {p^\kappa \over \pi }\pp{\pi \theta}{t}_{Diabatic} |
\pp{T}{t}_{Diabatic} = \frac{p^\kappa}{\pi}\pp{\pi \theta}{t}_{Diabatic} |
2621 |
\] |
\] |
2622 |
where $\theta = T/p^\kappa$. Thus, {\bf DIABT} may be written as |
where $\theta = T/p^\kappa$. Thus, {\bf DIABT} may be written as |
2623 |
\[ |
\[ |
2624 |
{\bf DIABT} = {p^\kappa \over \pi } \left( \pp{\pi \theta}{t}_{Diabatic} + \pp{\pi \theta}{t}_{Analysis} \right) |
{\bf DIABT} = \frac{p^\kappa}{\pi} \left( \pp{\pi \theta}{t}_{Diabatic} + \pp{\pi \theta}{t}_{Analysis} \right) |
2625 |
\] |
\] |
2626 |
\\ |
\\ |
2627 |
|
|
2640 |
\] |
\] |
2641 |
then, since there are no surface pressure changes due to Diabatic processes, we may write |
then, since there are no surface pressure changes due to Diabatic processes, we may write |
2642 |
\[ |
\[ |
2643 |
\pp{q}{t}_{Diabatic} = {1 \over \pi }\pp{\pi q}{t}_{Diabatic} |
\pp{q}{t}_{Diabatic} = \frac{1}{\pi}\pp{\pi q}{t}_{Diabatic} |
2644 |
\] |
\] |
2645 |
Thus, {\bf DIABQ} may be written as |
Thus, {\bf DIABQ} may be written as |
2646 |
\[ |
\[ |
2647 |
{\bf DIABQ} = {1 \over \pi } \left( \pp{\pi q}{t}_{Diabatic} + \pp{\pi q}{t}_{Analysis} \right) |
{\bf DIABQ} = \frac{1}{\pi} \left( \pp{\pi q}{t}_{Diabatic} + \pp{\pi q}{t}_{Analysis} \right) |
2648 |
\] |
\] |
2649 |
\\ |
\\ |
2650 |
|
|
2658 |
\[ |
\[ |
2659 |
{\bf VINTUQ} = \frac{ \int_{surf}^{top} u q \rho dz } { \int_{surf}^{top} \rho dz } |
{\bf VINTUQ} = \frac{ \int_{surf}^{top} u q \rho dz } { \int_{surf}^{top} \rho dz } |
2660 |
\] |
\] |
2661 |
Using $\rho \delta z = -{\delta p \over g} = - {1 \over g} \delta p$, we have |
Using $\rho \delta z = -\frac{\delta p}{g} = - \frac{1}{g} \delta p$, we have |
2662 |
\[ |
\[ |
2663 |
{\bf VINTUQ} = { \int_0^1 u q dp } |
{\bf VINTUQ} = { \int_0^1 u q dp } |
2664 |
\] |
\] |
2675 |
\[ |
\[ |
2676 |
{\bf VINTVQ} = \frac{ \int_{surf}^{top} v q \rho dz } { \int_{surf}^{top} \rho dz } |
{\bf VINTVQ} = \frac{ \int_{surf}^{top} v q \rho dz } { \int_{surf}^{top} \rho dz } |
2677 |
\] |
\] |
2678 |
Using $\rho \delta z = -{\delta p \over g} = - {1 \over g} \delta p$, we have |
Using $\rho \delta z = -\frac{\delta p}{g} = - \frac{1}{g} \delta p$, we have |
2679 |
\[ |
\[ |
2680 |
{\bf VINTVQ} = { \int_0^1 v q dp } |
{\bf VINTVQ} = { \int_0^1 v q dp } |
2681 |
\] |
\] |
2708 |
\[ |
\[ |
2709 |
{\bf VINTVT} = \frac{ \int_{surf}^{top} v T \rho dz } { \int_{surf}^{top} \rho dz } |
{\bf VINTVT} = \frac{ \int_{surf}^{top} v T \rho dz } { \int_{surf}^{top} \rho dz } |
2710 |
\] |
\] |
2711 |
Using $\rho \delta z = -{\delta p \over g} $, we have |
Using $\rho \delta z = -\frac{\delta p}{g} $, we have |
2712 |
\[ |
\[ |
2713 |
{\bf VINTVT} = { \int_0^1 v T dp } |
{\bf VINTVT} = { \int_0^1 v T dp } |
2714 |
\] |
\] |
2773 |
given by: |
given by: |
2774 |
\begin{eqnarray*} |
\begin{eqnarray*} |
2775 |
{\bf QINT} & = & \int_{surf}^{top} \rho q dz \\ |
{\bf QINT} & = & \int_{surf}^{top} \rho q dz \\ |
2776 |
& = & {\pi \over g} \int_0^1 q dp |
& = & \frac{\pi}{g} \int_0^1 q dp |
2777 |
\end{eqnarray*} |
\end{eqnarray*} |
2778 |
where we have used the hydrostatic relation |
where we have used the hydrostatic relation |
2779 |
$\rho \delta z = -{\delta p \over g} $. |
$\rho \delta z = -\frac{\delta p}{g} $. |
2780 |
\\ |
\\ |
2781 |
|
|
2782 |
|
|
2786 |
\noindent |
\noindent |
2787 |
The u-wind at the 2-meter depth is determined from the similarity theory: |
The u-wind at the 2-meter depth is determined from the similarity theory: |
2788 |
\[ |
\[ |
2789 |
{\bf U2M} = {u_* \over k} \psi_{m_{2m}} {u_{sl} \over {W_s}} = |
{\bf U2M} = \frac{u_*}{k} \psi_{m_{2m}} \frac{u_{sl}}{W_s} = |
2790 |
{ \psi_{m_{2m}} \over {\psi_{m_{sl}} }}u_{sl} |
\frac{ \psi_{m_{2m}} }{ \psi_{m_{sl}} }u_{sl} |
2791 |
\] |
\] |
2792 |
|
|
2793 |
\noindent |
\noindent |
2802 |
\noindent |
\noindent |
2803 |
The v-wind at the 2-meter depth is a determined from the similarity theory: |
The v-wind at the 2-meter depth is a determined from the similarity theory: |
2804 |
\[ |
\[ |
2805 |
{\bf V2M} = {u_* \over k} \psi_{m_{2m}} {v_{sl} \over {W_s}} = |
{\bf V2M} = \frac{u_*}{k} \psi_{m_{2m}} \frac{v_{sl}}{W_s} = |
2806 |
{ \psi_{m_{2m}} \over {\psi_{m_{sl}} }}v_{sl} |
\frac{ \psi_{m_{2m}} }{ \psi_{m_{sl}} }v_{sl} |
2807 |
\] |
\] |
2808 |
|
|
2809 |
\noindent |
\noindent |
2818 |
\noindent |
\noindent |
2819 |
The temperature at the 2-meter depth is a determined from the similarity theory: |
The temperature at the 2-meter depth is a determined from the similarity theory: |
2820 |
\[ |
\[ |
2821 |
{\bf T2M} = P^{\kappa} ({\theta* \over k} ({\psi_{h_{2m}}+\psi_g}) + \theta_{surf} ) = |
{\bf T2M} = P^{\kappa} (\frac{\theta*}{k} ({\psi_{h_{2m}}+\psi_g}) + \theta_{surf} ) = |
2822 |
P^{\kappa}(\theta_{surf} + { {\psi_{h_{2m}}+\psi_g} \over {{\psi_{h_{sl}}+\psi_g}} } |
P^{\kappa}(\theta_{surf} + \frac{ \psi_{h_{2m}}+\psi_g }{ \psi_{h_{sl}}+\psi_g } |
2823 |
(\theta_{sl} - \theta_{surf})) |
(\theta_{sl} - \theta_{surf}) ) |
2824 |
\] |
\] |
2825 |
where: |
where: |
2826 |
\[ |
\[ |
2827 |
\theta_* = - { (\overline{w^{\prime}\theta^{\prime}}) \over {u_*} } |
\theta_* = - \frac{ (\overline{w^{\prime}\theta^{\prime}}) }{ u_* } |
2828 |
\] |
\] |
2829 |
|
|
2830 |
\noindent |
\noindent |
2840 |
\noindent |
\noindent |
2841 |
The specific humidity at the 2-meter depth is determined from the similarity theory: |
The specific humidity at the 2-meter depth is determined from the similarity theory: |
2842 |
\[ |
\[ |
2843 |
{\bf Q2M} = P^{\kappa} ({q_* \over k} ({\psi_{h_{2m}}+\psi_g}) + q_{surf} ) = |
{\bf Q2M} = P^{\kappa} \frac({q_*}{k} ({\psi_{h_{2m}}+\psi_g}) + q_{surf} ) = |
2844 |
P^{\kappa}(q_{surf} + { {\psi_{h_{2m}}+\psi_g} \over {{\psi_{h_{sl}}+\psi_g}} } |
P^{\kappa}(q_{surf} + \frac{ \psi_{h_{2m}}+\psi_g }{ \psi_{h_{sl}}+\psi_g } |
2845 |
(q_{sl} - q_{surf})) |
(q_{sl} - q_{surf})) |
2846 |
\] |
\] |
2847 |
where: |
where: |
2848 |
\[ |
\[ |
2849 |
q_* = - { (\overline{w^{\prime}q^{\prime}}) \over {u_*} } |
q_* = - \frac{ (\overline{w^{\prime}q^{\prime}}) }{ u_* } |
2850 |
\] |
\] |
2851 |
|
|
2852 |
\noindent |
\noindent |
2864 |
and the model lowest level wind using the ratio of the non-dimensional wind shear |
and the model lowest level wind using the ratio of the non-dimensional wind shear |
2865 |
at the two levels: |
at the two levels: |
2866 |
\[ |
\[ |
2867 |
{\bf U10M} = {u_* \over k} \psi_{m_{10m}} {u_{sl} \over {W_s}} = |
{\bf U10M} = \frac{u_*}{k} \psi_{m_{10m}} \frac{u_{sl}}{W_s} = |
2868 |
{ \psi_{m_{10m}} \over {\psi_{m_{sl}} }}u_{sl} |
\frac{ \psi_{m_{10m}} }{ \psi_{m_{sl}} }u_{sl} |
2869 |
\] |
\] |
2870 |
|
|
2871 |
\noindent |
\noindent |
2881 |
and the model lowest level wind using the ratio of the non-dimensional wind shear |
and the model lowest level wind using the ratio of the non-dimensional wind shear |
2882 |
at the two levels: |
at the two levels: |
2883 |
\[ |
\[ |
2884 |
{\bf V10M} = {u_* \over k} \psi_{m_{10m}} {v_{sl} \over {W_s}} = |
{\bf V10M} = \frac{u_*}{k} \psi_{m_{10m}} \frac{v_{sl}}{W_s} = |
2885 |
{ \psi_{m_{10m}} \over {\psi_{m_{sl}} }}v_{sl} |
\frac{ \psi_{m_{10m}} }{ \psi_{m_{sl}} }v_{sl} |
2886 |
\] |
\] |
2887 |
|
|
2888 |
\noindent |
\noindent |
2898 |
temperature and the model lowest level potential temperature using the ratio of the |
temperature and the model lowest level potential temperature using the ratio of the |
2899 |
non-dimensional temperature gradient at the two levels: |
non-dimensional temperature gradient at the two levels: |
2900 |
\[ |
\[ |
2901 |
{\bf T10M} = P^{\kappa} ({\theta* \over k} ({\psi_{h_{10m}}+\psi_g}) + \theta_{surf} ) = |
{\bf T10M} = P^{\kappa} (\frac{\theta*}{k} ({\psi_{h_{10m}}+\psi_g}) + \theta_{surf} ) = |
2902 |
P^{\kappa}(\theta_{surf} + { {\psi_{h_{10m}}+\psi_g} \over {{\psi_{h_{sl}}+\psi_g}} } |
P^{\kappa}(\theta_{surf} + \frac{\psi_{h_{10m}}+\psi_g}{\psi_{h_{sl}}+\psi_g} |
2903 |
(\theta_{sl} - \theta_{surf})) |
(\theta_{sl} - \theta_{surf})) |
2904 |
\] |
\] |
2905 |
where: |
where: |
2906 |
\[ |
\[ |
2907 |
\theta_* = - { (\overline{w^{\prime}\theta^{\prime}}) \over {u_*} } |
\theta_* = - \frac{ (\overline{w^{\prime}\theta^{\prime}}) }{ u_* } |
2908 |
\] |
\] |
2909 |
|
|
2910 |
\noindent |
\noindent |
2921 |
humidity and the model lowest level specific humidity using the ratio of the |
humidity and the model lowest level specific humidity using the ratio of the |
2922 |
non-dimensional temperature gradient at the two levels: |
non-dimensional temperature gradient at the two levels: |
2923 |
\[ |
\[ |
2924 |
{\bf Q10M} = P^{\kappa} ({q_* \over k} ({\psi_{h_{10m}}+\psi_g}) + q_{surf} ) = |
{\bf Q10M} = P^{\kappa} (\frac{q_*}{k} ({\psi_{h_{10m}}+\psi_g}) + q_{surf} ) = |
2925 |
P^{\kappa}(q_{surf} + { {\psi_{h_{10m}}+\psi_g} \over {{\psi_{h_{sl}}+\psi_g}} } |
P^{\kappa}(q_{surf} + \frac{\psi_{h_{10m}}+\psi_g}{\psi_{h_{sl}}+\psi_g} |
2926 |
(q_{sl} - q_{surf})) |
(q_{sl} - q_{surf})) |
2927 |
\] |
\] |
2928 |
where: |
where: |
2929 |
\[ |
\[ |
2930 |
q_* = - { (\overline{w^{\prime}q^{\prime}}) \over {u_*} } |
q_* = - \frac{ (\overline{w^{\prime}q^{\prime}}) }{ u_* } |
2931 |
\] |
\] |
2932 |
|
|
2933 |
\noindent |
\noindent |
2968 |
\] |
\] |
2969 |
|
|
2970 |
|
|
2971 |
\subsection{Key subroutines, parameters and files} |
\subsubsection{Key subroutines, parameters and files} |
2972 |
|
|
2973 |
|
\subsubsection{Dos and donts} |
2974 |
|
|
2975 |
|
\subsubsection{Fizhi Reference} |
2976 |
|
|
2977 |
|
\subsubsection{Experiments and tutorials that use fizhi} |
2978 |
|
\label{sec:pkg:fizhi:experiments} |
2979 |
|
|
2980 |
\subsection{Dos and donts} |
\begin{itemize} |
2981 |
|
\item{Global atmosphere experiment with realistic SST and topography in fizhi-cs-32x32x10 verification directory. } |
2982 |
|
\item{Global atmosphere aqua planet experiment in fizhi-cs-aqualev20 verification directory. } |
2983 |
|
\end{itemize} |
2984 |
|
|
|
\subsection{Fizhi Reference} |
|